| Best model | name | model_type | metric_type | metric_value | train_time |
|---|---|---|---|---|---|
| 1_Baseline | Baseline | logloss | 0.250002 | 2.73 | |
| 2_DecisionTree | Decision Tree | logloss | 0.222161 | 133.45 | |
| 3_Default_Xgboost | Xgboost | logloss | 0.201696 | 129.52 | |
| 4_Default_NeuralNetwork | Neural Network | logloss | 0.235937 | 144.3 | |
| 5_Default_RandomForest | Random Forest | logloss | 0.221147 | 603.16 | |
| 3_Default_Xgboost_GoldenFeatures | Xgboost | logloss | 0.201963 | 129.47 | |
| 2_DecisionTree_GoldenFeatures | Decision Tree | logloss | 0.219555 | 129.2 | |
| 4_Default_NeuralNetwork_GoldenFeatures | Neural Network | logloss | 0.236634 | 149.24 | |
| the best | Ensemble | Ensemble | logloss | 0.201486 | 8.39 |
logloss
1.8 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.250002 | nan |
| auc | 0.5 | nan |
| f1 | 0.128392 | 0.06173 |
| accuracy | 0.0686 | 0.06173 |
| precision | 0.0686 | 0.06173 |
| recall | 1 | 0.06173 |
| mcc | 0 | 0.06173 |
| score | threshold | |
|---|---|---|
| logloss | 0.250002 | nan |
| auc | 0.5 | nan |
| f1 | 0.128392 | 0.06173 |
| accuracy | 0.0686 | 0.06173 |
| precision | 0.0686 | 0.06173 |
| recall | 1 | 0.06173 |
| mcc | 0 | 0.06173 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 0 | 55884 |
| Labeled as 1 | 0 | 4116 |
logloss
132.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.222161 | nan |
| auc | 0.749963 | nan |
| f1 | 0.309402 | 0.126857 |
| accuracy | 0.922717 | 0.32701 |
| precision | 0.363111 | 0.32701 |
| recall | 1 | 0.00126478 |
| mcc | 0.254071 | 0.126857 |
| score | threshold | |
|---|---|---|
| logloss | 0.222161 | nan |
| auc | 0.749963 | nan |
| f1 | 0.229606 | 0.32701 |
| accuracy | 0.922717 | 0.32701 |
| precision | 0.363111 | 0.32701 |
| recall | 0.167881 | 0.32701 |
| mcc | 0.210869 | 0.32701 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 54672 | 1212 |
| Labeled as 1 | 3425 | 691 |
logloss
128.2 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.219555 | nan |
| auc | 0.751138 | nan |
| f1 | 0.328546 | 0.126878 |
| accuracy | 0.927117 | 0.346464 |
| precision | 0.326457 | 0.126878 |
| recall | 1 | 0.00198572 |
| mcc | 0.278758 | 0.126878 |
| score | threshold | |
|---|---|---|
| logloss | 0.219555 | nan |
| auc | 0.751138 | nan |
| f1 | 0.0581521 | 0.346464 |
| accuracy | 0.927117 | 0.346464 |
| precision | 0.256167 | 0.346464 |
| recall | 0.0327988 | 0.346464 |
| mcc | 0.0698508 | 0.346464 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 55492 | 392 |
| Labeled as 1 | 3981 | 135 |
logloss
128.3 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.201696 | nan |
| auc | 0.822041 | nan |
| f1 | 0.347872 | 0.175639 |
| accuracy | 0.93075 | 0.44077 |
| precision | 0.467446 | 0.44077 |
| recall | 1 | 0.000553567 |
| mcc | 0.295999 | 0.175639 |
| score | threshold | |
|---|---|---|
| logloss | 0.201696 | nan |
| auc | 0.822041 | nan |
| f1 | 0.11877 | 0.44077 |
| accuracy | 0.93075 | 0.44077 |
| precision | 0.467446 | 0.44077 |
| recall | 0.0680272 | 0.44077 |
| mcc | 0.15845 | 0.44077 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 55565 | 319 |
| Labeled as 1 | 3836 | 280 |
logloss
128.4 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.201963 | nan |
| auc | 0.82174 | nan |
| f1 | 0.34556 | 0.174912 |
| accuracy | 0.930417 | 0.438242 |
| precision | 0.450751 | 0.438242 |
| recall | 1 | 0.000616663 |
| mcc | 0.293573 | 0.145551 |
| score | threshold | |
|---|---|---|
| logloss | 0.201963 | nan |
| auc | 0.82174 | nan |
| f1 | 0.114528 | 0.438242 |
| accuracy | 0.930417 | 0.438242 |
| precision | 0.450751 | 0.438242 |
| recall | 0.0655977 | 0.438242 |
| mcc | 0.151817 | 0.438242 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 55555 | 329 |
| Labeled as 1 | 3846 | 270 |
logloss
143.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.235937 | nan |
| auc | 0.694712 | nan |
| f1 | 0.211239 | 0.116338 |
| accuracy | 0.66195 | 0.116338 |
| precision | 0.125747 | 0.116338 |
| recall | 1 | 7.56648e-05 |
| mcc | 0.170984 | 0.108263 |
| score | threshold | |
|---|---|---|
| logloss | 0.235937 | nan |
| auc | 0.694712 | nan |
| f1 | 0.211239 | 0.116338 |
| accuracy | 0.66195 | 0.116338 |
| precision | 0.125747 | 0.116338 |
| recall | 0.659864 | 0.116338 |
| mcc | 0.169553 | 0.116338 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 37001 | 18883 |
| Labeled as 1 | 1400 | 2716 |
logloss
148.0 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.236634 | nan |
| auc | 0.680723 | nan |
| f1 | 0.197464 | 0.0975385 |
| accuracy | 0.551717 | 0.0975385 |
| precision | 0.112555 | 0.0975385 |
| recall | 1 | 4.59745e-06 |
| mcc | 0.170441 | 0.0975385 |
| score | threshold | |
|---|---|---|
| logloss | 0.236634 | nan |
| auc | 0.680723 | nan |
| f1 | 0.197464 | 0.0975385 |
| accuracy | 0.551717 | 0.0975385 |
| precision | 0.112555 | 0.0975385 |
| recall | 0.803936 | 0.0975385 |
| mcc | 0.170441 | 0.0975385 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 29794 | 26090 |
| Labeled as 1 | 807 | 3309 |
logloss
602.1 seconds
| score | threshold | |
|---|---|---|
| logloss | 0.221147 | nan |
| auc | 0.761092 | nan |
| f1 | 0.308757 | 0.205884 |
| accuracy | 0.9292 | 0.333517 |
| precision | 0.424138 | 0.333517 |
| recall | 1 | 0.00588364 |
| mcc | 0.253586 | 0.205884 |
| score | threshold | |
|---|---|---|
| logloss | 0.221147 | nan |
| auc | 0.761092 | nan |
| f1 | 0.148014 | 0.333517 |
| accuracy | 0.9292 | 0.333517 |
| precision | 0.424138 | 0.333517 |
| recall | 0.0896501 | 0.333517 |
| mcc | 0.170613 | 0.333517 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 55383 | 501 |
| Labeled as 1 | 3747 | 369 |
| Model | Weight |
|---|---|
| 3_Default_Xgboost | 3 |
| 3_Default_Xgboost_GoldenFeatures | 2 |
| score | threshold | |
|---|---|---|
| logloss | 0.201486 | nan |
| auc | 0.822858 | nan |
| f1 | 0.347314 | 0.175358 |
| accuracy | 0.930417 | 0.438295 |
| precision | 0.450751 | 0.438295 |
| recall | 1 | 0.000620673 |
| mcc | 0.297133 | 0.145456 |
| score | threshold | |
|---|---|---|
| logloss | 0.201486 | nan |
| auc | 0.822858 | nan |
| f1 | 0.114528 | 0.438295 |
| accuracy | 0.930417 | 0.438295 |
| precision | 0.450751 | 0.438295 |
| recall | 0.0655977 | 0.438295 |
| mcc | 0.151817 | 0.438295 |
| Predicted as 0 | Predicted as 1 | |
|---|---|---|
| Labeled as 0 | 55555 | 329 |
| Labeled as 1 | 3846 | 270 |